Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 992 394 778 968 601 178 492 223 753 507 26 388 409 249 113 379 51 319 799 160
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 319 601 NA NA 409 113 507 NA 992 753 249 799 26 492 160 379 223 778 51 968 394 178 388
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 5 3 1 5 1 2 5 1 2 1
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w"
[24] "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W"
[24] "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "c" "l" "z" "d" "q" "H" "G" "Z" "P" "Y"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 1 4
which( manyNumbersWithNA > 900 )
[1] 9 20
which( is.na( manyNumbersWithNA ) )
[1] 3 4 8
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 992 968
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 992 968
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 992 968
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "H" "G" "Z" "P" "Y"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "c" "l" "z" "d" "q"
manyNumbers %in% 300:600
[1] FALSE TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE FALSE TRUE TRUE FALSE FALSE
[16] TRUE FALSE TRUE FALSE FALSE
which( manyNumbers %in% 300:600 )
[1] 2 7 10 12 13 16 18
sum( manyNumbers %in% 300:600 )
[1] 7
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "small" "large" NA NA "small" "small" "large" NA "large" "large" "small"
[12] "large" "small" "small" "small" "small" "small" "large" "small" "large" "small" "small"
[23] "small"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "small" "large" "UNKNOWN" "UNKNOWN" "small" "small" "large" "UNKNOWN" "large"
[10] "large" "small" "large" "small" "small" "small" "small" "small" "large"
[19] "small" "large" "small" "small" "small"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 0 601 NA NA 0 0 507 NA 992 753 0 799 0 0 0 0 0 778 0 968 0 0 0
unique( duplicatedNumbers )
[1] 5 3 1 2
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 5 3 1 2
duplicated( duplicatedNumbers )
[1] FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 9
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 992
which.min( manyNumbersWithNA )
[1] 13
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 26
range( manyNumbersWithNA, na.rm = TRUE )
[1] 26 992
manyNumbersWithNA
[1] 319 601 NA NA 409 113 507 NA 992 753 249 799 26 492 160 379 223 778 51 968 394 178 388
sort( manyNumbersWithNA )
[1] 26 51 113 160 178 223 249 319 379 388 394 409 492 507 601 753 778 799 968 992
sort( manyNumbersWithNA, na.last = TRUE )
[1] 26 51 113 160 178 223 249 319 379 388 394 409 492 507 601 753 778 799 968 992 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 992 968 799 778 753 601 507 492 409 394 388 379 319 249 223 178 160 113 51 26 NA NA NA
manyNumbersWithNA[1:5]
[1] 319 601 NA NA 409
order( manyNumbersWithNA[1:5] )
[1] 1 5 2 3 4
rank( manyNumbersWithNA[1:5] )
[1] 1 3 4 5 2
sort( mixedLetters )
[1] "c" "d" "G" "H" "l" "P" "q" "Y" "z" "Z"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 8.5 8.5 10.0 1.0 2.5 6.0 6.0 6.0 4.0 2.5
rank( manyDuplicates, ties.method = "min" )
[1] 8 8 10 1 2 5 5 5 4 2
rank( manyDuplicates, ties.method = "random" )
[1] 8 9 10 1 2 5 7 6 4 3
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.00000000 -0.50000000 0.00000000 0.50000000 1.00000000 0.75025362 0.06789689
[8] -1.43082598 -0.69610590 -0.74646126 -0.65090974 0.29244999 1.73448191 1.78574121
[15] -0.91039611
round( v, 0 )
[1] -1 0 0 0 1 1 0 -1 -1 -1 -1 0 2 2 -1
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 0.8 0.1 -1.4 -0.7 -0.7 -0.7 0.3 1.7 1.8 -0.9
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 0.75 0.07 -1.43 -0.70 -0.75 -0.65 0.29 1.73 1.79 -0.91
floor( v )
[1] -1 -1 0 0 1 0 0 -2 -1 -1 -1 0 1 1 -1
ceiling( v )
[1] -1 0 0 1 1 1 1 -1 0 0 0 1 2 2 0
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 x 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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